Methodology

We collect data from the browsers of site visitors to our exclusive on-demand network of analytics and social bookmarking products. We count sessions to our network sites, which are defined as a user active on a site with no more than a 30 minute inactive period. A user can have multiple sessions per day. The data is compiled from approximately 100 million valid sessions per month, widely distributed over thousands of websites. The information published is an aggregation of the data from this network of hosted websites. In addition, we classify 430+ referral sources identified as search engines. Aggregate traffic referrals from these engines are summarized and reported monthly. The statistics for search engines include both organic and sponsored referrals.

This data provides valuable insight into significant trends for internet usage. These statistics include monthly information on key statistics such as browser trends (e.g. Internet Explorer vs. Chrome market share), search engine referral data (e.g. Yahoo vs. Bing vs. Google traffic market share) and operating system share (Windows vs. Mac vs. Linux market share or iOS market share vs. Android).

Additional estimates about the website population:

• 76% participate in pay per click programs to drive traffic to their sites.
• 43% are commerce sites
• 18% are corporate sites
• 10% are content sites
• 29% classify themselves as other (includes gov, org, search engine marketers etc.)

Competing methodologies are not as accurate as using global analytics data. Competing methods include:

Surveys or Panels: The results from a survey are based on a subset of the general internet population (those willing and able to take surveys). Also, surveys are generally not provided in all languages and for all regions. This can skew the results significantly.

ISP data: While the amount of ISP data can be voluminous, ISPs are regional. So, unless the ISP data is an aggregation of all ISPs, there will be a built in regional bias to the market share reports.

Toolbars or Other Tracking Components Installed on Computers: Since the components would need to be developed identically for every possible platform and language and distributed evenly across all platforms and regions, this collection method is inherently flawed.

A large and growing percentage of web traffic is generated by bots and toolbars. This data is not included in our statistics. We employ a variety of techniques to detect which sessions are invalid. See our page on detection methods here.

A significant percentage of web pages loaded are never visible.

For a variety of reasons, pages downloaded from the web are often not visible on the user's device. This can skew the usage share data since the amount of hidden pages varies by browser and platform. See our page on detection methods here.

We have implemented country-level weighting in our reports. This means that we adjust our reports proportionally based on how much traffic we record from a country vs. how many internet users that country has. For example, although we have significant data from China, it is relatively small compared to the number of internet users in China. Therefore, we weight Chinese traffic proportionally higher in our global reports. This change produces a much more accurate view of worldwide usage share statistics.

The source of the weighting data is C.I.A published statistics and InternetLiveStats.com.

When new data is published from our sources, it may lead to significant changes to trends. For example, India is experiencing significant growth in internet users, and when these changes are applied, India-specific usage share will have an affect on the global usage share statistics.